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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
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Federal AI Intelligence · U.S. Government AI Observatory

Federal AI landscape: executive briefing

Filtered: stage = unknown; function = forecasting

Generated 2026-10-12 08:02 UTCDataset: 2025 Federal Agency AI Use Case Inventory (individually reported use cases), Office of Management and Budget (OMB). Version 2025-inventory@62d5baa65fa3, processed 2026-10-11, rules 2026.10.1. Static snapshot.Applied filters: stage = unknown; function = forecasting · 12 records

Key findings

  • 12 use-case records from 2 agencies: 0 deployed (0%), 0 pilots, 0 in development or acquisition, 0 retired, 12 with no stage reported.
  • 0 records are designated high-impact; 0 of them (n/a) answered at least one minimum-practice question.
  • Sourcing is reported for 0% of use cases. Where reported, n/a involve in-house development.
  • 12 use cases (100%) have no reported development stage.

Lifecycle

StageRecordsShare
Not reported12100%

AI technology

ClassificationRecordsShareDeployed
Not reported12100%0

Agencies

AgencyRecordsDeployedHigh-impactCompleteness
DOC · Department of Commerce10000%
TVA · Tennessee Valley Authority20017%

High-impact designation

DesignationRecords
Not reported12

Governance evidence: use cases designated high-impact

PracticeIn placeIn progressNot in placeN/A or precludedOtherNo answerIn scope
Pre-deployment testing0000000
AI impact assessment0000000
Independent review0000000
Ongoing monitoring0000000
Operator training0000000
Fail-safe0000000
Appeal process0000000
User and public consultation0000000

"In place" means the agency reported the practice as established. "No answer" means the field was blank; it says nothing about whether the practice exists.

Method

All figures are computed directly from the normalised inventory records. Category labels are normalised from the source answer options; original values are kept on each record. Governance answers are classified as in place, in progress, not in place, not applicable, precluded, waived, other or no answer, and blanks are never read as "no". See the Methodology page for full rules.

Limitations

  • Figures are what agencies reported in the 2025 inventory. They are not verified, and registration of use cases is not complete for every agency.
  • A blank answer is missing evidence, not evidence that a practice or safeguard is absent.
  • Counts are use-case records. A larger portfolio does not indicate better performance or greater AI maturity, and agencies differ in how they split systems into use cases.
  • The inventory has no budget, cost, accuracy or outcome data. None is shown or inferred here.
  • This is a disclosure analysis. It is not an audit, a compliance determination or an official government assessment.

Source records

All 12 records.

RecordAgency IDAgencyUse caseStage
R1114TVALoad ForecastingNot reported
R1118TVARiver ForecastNot reported
R2909DOC-24DOCEvaluate AI for Forecasting FrontsNot reported
R2910DOC-25DOCAI-Driven Global Forecast Model and EnsembleNot reported
R2914DOC-29DOCEnhanced Precipitation ForecastingNot reported
R2916DOC-31DOCEnhanced Fire Weather, Aviation, and Storm Surge Forecast GuidanceNot reported
R2998DOC-141DOCAdvancing the West Coast Ocean Forecasting System through Assessment, Model Development, and Ecological ProductsNot reported
R3007DOC-149DOCThe VOLcanic Cloud Analysis Toolkit (VOLCAT): An application system for detecting, tracking, characterizing, and forecasting hazardous volcanic eventsNot reported
R3012DOC-154DOCWork with Allen Institute on developing the Ai2 Climate Emulator (ACE) for seamless weather applications, including to emulate SHiELD-based medium-range forecasts for large ensemble predictionsNot reported
R3023DOC-165DOCA hybrid physics-machine learning model for orographic precipitation forecastingNot reported
R3025DOC-167DOCSevere Convective Weather Parameter Generation using AI/ML with Microwave/Infrared Sounder Satellite Observations for Enhanced Weather Analysis and ForecastNot reported
R3050DOC-192DOCAI-Driven Predictive Maintenance for the NOAA FleetNot reported

Prepared with Federal AI Intelligence by Irakli Petriashvili. Source: https://github.com/ombegov/2025-Federal-Agency-AI-Use-Case-Inventory